Determination of user intention-based representations of internet resource identification items and selection of content items

ABSTRACT

One or more computing devices, systems, and/or methods are provided. In an example, an internet resource identification item associated with one or more internet resources may be identified. User activity information associated with a plurality of events may be analyzed to determine a plurality of sets of text associated with the internet resource identification item, wherein each set of text of the plurality of sets of text is associated with an event, of the plurality of events, associated with an internet resource of the one or more internet resources. A plurality of term representations may be determined based upon the plurality of sets of text. A user intention-based representation associated with the internet resource identification item may be generated based upon the plurality of term representations. A content item may be selected for presentation via a client device based upon the user intention-based representation.

RELATED APPLICATION

This application claims priority to and is a continuation of U.S.application Ser. No. 17/719,408, filed on Apr. 13, 2022, entitled“DETERMINATION OF USER INTENTION-BASED REPRESENTATIONS OF INTERNETRESOURCE IDENTIFICATION ITEMS AND SELECTION OF CONTENT ITEMS”, which isincorporated by reference herein in its entirety.

BACKGROUND

Many services, such as websites, applications, etc. may provideplatforms for viewing media. For example, a user may interact with aservice. While interacting with the service, selected media may bepresented to the user automatically.

SUMMARY

In accordance with the present disclosure, one or more computing devicesand/or methods are provided. In an example, a first internet resourceidentification item associated with one or more first internet resourcesmay be identified. User activity information associated with a pluralityof events may be analyzed to determine a plurality of search queriesassociated with the first internet resource identification item, whereineach search query of the plurality of search queries is associated withan event, of the plurality of events, in which an internet resource ofthe one or more first internet resources is accessed via a selection ofa search result from among search results generated based upon thesearch query. A plurality of term representations may be determinedbased upon the plurality of search queries, wherein the plurality ofterm representations comprises one or more first term representations ofone or more first terms of a first search query of the plurality ofsearch queries and/or one or more second term representations of one ormore second terms of a second search query of the plurality of searchqueries. A first user intention-based representation associated with thefirst internet resource identification item may be generated based uponthe plurality of term representations. A first content item may beselected for presentation via a first client device based upon the firstuser intention-based representation.

In an example, a first internet resource identification item associatedwith one or more first internet resources may be identified. Useractivity information associated with a plurality of events may beanalyzed to determine a plurality of sets of text associated with thefirst internet resource identification item, wherein each set of text ofthe plurality of sets of text is associated with an event, of theplurality of events, associated with an internet resource of the one ormore first internet resources. A plurality of term representations maybe determined based upon the plurality of sets of text, wherein theplurality of term representations comprises one or more first termrepresentations of one or more first terms of a first set of text of theplurality of sets of text and/or one or more second term representationsof one or more second terms of a second set of text of the plurality ofsets of text. A first user intention-based representation associatedwith the first internet resource identification item may be generatedbased upon the plurality of term representations. A first content itemmay be selected for presentation via a first client device based uponthe first user intention-based representation.

DESCRIPTION OF THE DRAWINGS

While the techniques presented herein may be embodied in alternativeforms, the particular embodiments illustrated in the drawings are only afew examples that are supplemental of the description provided herein.These embodiments are not to be interpreted in a limiting manner, suchas limiting the claims appended hereto.

FIG. 1 is an illustration of a scenario involving various examples ofnetworks that may connect servers and clients.

FIG. 2 is an illustration of a scenario involving an exampleconfiguration of a server that may utilize and/or implement at least aportion of the techniques presented herein.

FIG. 3 is an illustration of a scenario involving an exampleconfiguration of a client that may utilize and/or implement at least aportion of the techniques presented herein.

FIG. 4 is a flow chart illustrating an example method for determininguser intention-based representations associated with internet resourceidentification items and/or selecting content for transmission todevices.

FIG. 5A is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where a first client device presents a firstweb page.

FIG. 5B is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where a first client device presents aplurality of search results.

FIG. 5C is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where a first client device presents a fourthweb page.

FIG. 5D is a component block diagram illustrating a representation of afirst search-to-click profile generated by an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices.

FIG. 5E is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where a first user intention-basedrepresentation is generated.

FIG. 5F is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where one or more sets of information areincluded in the first profile.

FIG. 5G is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where a first client device transmits a requestto access a resource to a server.

FIG. 5H is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where a first server transmits a first requestfor content to a second server associated with a content system.

FIG. 5I is a component block diagram illustrating an example system fordetermining user intention-based representations associated withinternet resource identification items and/or selecting content fortransmission to devices, where a first client device presents and/oraccesses a seventh web page.

FIG. 6 is a flow chart illustrating an example method for determininguser intention-based representations associated with internet resourceidentification items and/or selecting content for transmission todevices.

FIG. 7 is an illustration of a scenario featuring an examplenon-transitory machine readable medium in accordance with one or more ofthe provisions set forth herein.

DETAILED DESCRIPTION

Subject matter will now be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, specific example embodiments. Thisdescription is not intended as an extensive or detailed discussion ofknown concepts. Details that are known generally to those of ordinaryskill in the relevant art may have been omitted, or may be handled insummary fashion.

The following subject matter may be embodied in a variety of differentforms, such as methods, devices, components, and/or systems.Accordingly, this subject matter is not intended to be construed aslimited to any example embodiments set forth herein. Rather, exampleembodiments are provided merely to be illustrative. Such embodimentsmay, for example, take the form of hardware, software, firmware or anycombination thereof.

1. Computing Scenario

The following provides a discussion of some types of computing scenariosin which the disclosed subject matter may be utilized and/orimplemented.

1.1. Networking

FIG. 1 is an interaction diagram of a scenario 100 illustrating aservice 102 provided by a set of servers 104 to a set of client devices110 via various types of networks. The servers 104 and/or client devices110 may be capable of transmitting, receiving, processing, and/orstoring many types of signals, such as in memory as physical memorystates.

The servers 104 of the service 102 may be internally connected via alocal area network 106 (LAN), such as a wired network where networkadapters on the respective servers 104 are interconnected via cables(e.g., coaxial and/or fiber optic cabling), and may be connected invarious topologies (e.g., buses, token rings, meshes, and/or trees). Theservers 104 may be interconnected directly, or through one or more othernetworking devices, such as routers, switches, and/or repeaters. Theservers 104 may utilize a variety of physical networking protocols(e.g., Ethernet and/or Fiber Channel) and/or logical networkingprotocols (e.g., variants of an Internet Protocol (IP), a TransmissionControl Protocol (TCP), and/or a User Datagram Protocol (UDP). The localarea network 106 may include, e.g., analog telephone lines, such as atwisted wire pair, a coaxial cable, full or fractional digital linesincluding T1, T2, T3, or T4 type lines, Integrated Services DigitalNetworks (ISDNs), Digital Subscriber Lines (DSLs), wireless linksincluding satellite links, or other communication links or channels,such as may be known to those skilled in the art. The local area network106 may be organized according to one or more network architectures,such as server/client, peer-to-peer, and/or mesh architectures, and/or avariety of roles, such as administrative servers, authenticationservers, security monitor servers, data stores for objects such as filesand databases, business logic servers, time synchronization servers,and/or front-end servers providing a user-facing interface for theservice 102.

Likewise, the local area network 106 may comprise one or moresub-networks, such as may employ differing architectures, may becompliant or compatible with differing protocols and/or may interoperatewithin the local area network 106. Additionally, a variety of local areanetworks 106 may be interconnected; e.g., a router may provide a linkbetween otherwise separate and independent local area networks 106.

In the scenario 100 of FIG. 1 , the local area network 106 of theservice 102 is connected to a wide area network 108 (WAN) that allowsthe service 102 to exchange data with other services 102 and/or clientdevices 110. The wide area network 108 may encompass variouscombinations of devices with varying levels of distribution andexposure, such as a public wide-area network (e.g., the Internet) and/ora private network (e.g., a virtual private network (VPN) of adistributed enterprise).

In the scenario 100 of FIG. 1 , the service 102 may be accessed via thewide area network 108 by a user 112 of one or more client devices 110,such as a portable media player (e.g., an electronic text reader, anaudio device, or a portable gaming, exercise, or navigation device); aportable communication device (e.g., a camera, a phone, a wearable or atext chatting device); a workstation; and/or a laptop form factorcomputer. The respective client devices 110 may communicate with theservice 102 via various connections to the wide area network 108. As afirst such example, one or more client devices 110 may comprise acellular communicator and may communicate with the service 102 byconnecting to the wide area network 108 via a wireless local areanetwork 106 provided by a cellular provider. As a second such example,one or more client devices 110 may communicate with the service 102 byconnecting to the wide area network 108 via a wireless local areanetwork 106 (and/or via a wired network) provided by a location such asthe user's home or workplace (e.g., a WiFi (Institute of Electrical andElectronics Engineers (IEEE) Standard 802.11) network or a Bluetooth(IEEE Standard 802.15.1) personal area network). In this manner, theservers 104 and the client devices 110 may communicate over varioustypes of networks. Other types of networks that may be accessed by theservers 104 and/or client devices 110 include mass storage, such asnetwork attached storage (NAS), a storage area network (SAN), or otherforms of computer or machine readable media.

1.2. Server Configuration

FIG. 2 presents a schematic architecture diagram 200 of a server 104that may utilize at least a portion of the techniques provided herein.Such a server 104 may vary widely in configuration or capabilities,alone or in conjunction with other servers, in order to provide aservice such as the service 102.

The server 104 may comprise one or more processors 210 that processinstructions. The one or more processors 210 may optionally include aplurality of cores; one or more coprocessors, such as a mathematicscoprocessor or an integrated graphical processing unit (GPU); and/or oneor more layers of local cache memory. The server 104 may comprise memory202 storing various forms of applications, such as an operating system204; one or more server applications 206, such as a hypertext transportprotocol (HTTP) server, a file transfer protocol (FTP) server, or asimple mail transport protocol (SMTP) server; and/or various forms ofdata, such as a database 208 or a file system. The server 104 maycomprise a variety of peripheral components, such as a wired and/orwireless network adapter 214 connectible to a local area network and/orwide area network; one or more storage components 216, such as a harddisk drive, a solid-state storage device (SSD), a flash memory device,and/or a magnetic and/or optical disk reader.

The server 104 may comprise a mainboard featuring one or morecommunication buses 212 that interconnect the processor 210, the memory202, and various peripherals, using a variety of bus technologies, suchas a variant of a serial or parallel AT Attachment (ATA) bus protocol; aUniform Serial Bus (USB) protocol; and/or Small Computer SystemInterface (SCI) bus protocol. In a multibus scenario, a communicationbus 212 may interconnect the server 104 with at least one other server.Other components that may optionally be included with the server 104(though not shown in the schematic diagram 200 of FIG. 2 ) include adisplay; a display adapter, such as a graphical processing unit (GPU);input peripherals, such as a keyboard and/or mouse; and a flash memorydevice that may store a basic input/output system (BIOS) routine thatfacilitates booting the server 104 to a state of readiness.

The server 104 may operate in various physical enclosures, such as adesktop or tower, and/or may be integrated with a display as an“all-in-one” device. The server 104 may be mounted horizontally and/orin a cabinet or rack, and/or may simply comprise an interconnected setof components. The server 104 may comprise a dedicated and/or sharedpower supply 218 that supplies and/or regulates power for the othercomponents. The server 104 may provide power to and/or receive powerfrom another server and/or other devices. The server 104 may comprise ashared and/or dedicated climate control unit 220 that regulates climateproperties, such as temperature, humidity, and/or airflow. Many suchservers 104 may be configured and/or adapted to utilize at least aportion of the techniques presented herein.

1.3. Client Device Configuration

FIG. 3 presents a schematic architecture diagram 300 of a client device110 whereupon at least a portion of the techniques presented herein maybe implemented. Such a client device 110 may vary widely inconfiguration or capabilities, in order to provide a variety offunctionality to a user such as the user 112. The client device 110 maybe provided in a variety of form factors, such as a desktop or towerworkstation; an “all-in-one” device integrated with a display 308; alaptop, tablet, convertible tablet, or palmtop device; a wearable devicemountable in a headset, eyeglass, earpiece, and/or wristwatch, and/orintegrated with an article of clothing; and/or a component of a piece offurniture, such as a tabletop, and/or of another device, such as avehicle or residence. The client device 110 may serve the user in avariety of roles, such as a workstation, kiosk, media player, gamingdevice, and/or appliance.

The client device 110 may comprise one or more processors 310 thatprocess instructions. The one or more processors 310 may optionallyinclude a plurality of cores; one or more coprocessors, such as amathematics coprocessor or an integrated graphical processing unit(GPU); and/or one or more layers of local cache memory. The clientdevice 110 may comprise memory 301 storing various forms ofapplications, such as an operating system 303; one or more userapplications 302, such as document applications, media applications,file and/or data access applications, communication applications such asweb browsers and/or email clients, utilities, and/or games; and/ordrivers for various peripherals. The client device 110 may comprise avariety of peripheral components, such as a wired and/or wirelessnetwork adapter 306 connectible to a local area network and/or wide areanetwork; one or more output components, such as a display 308 coupledwith a display adapter (optionally including a graphical processing unit(GPU)), a sound adapter coupled with a speaker, and/or a printer; inputdevices for receiving input from the user, such as a keyboard 311, amouse, a microphone, a camera, and/or a touch-sensitive component of thedisplay 308; and/or environmental sensors, such as a global positioningsystem (GPS) receiver 319 that detects the location, velocity, and/oracceleration of the client device 110, a compass, accelerometer, and/orgyroscope that detects a physical orientation of the client device 110.Other components that may optionally be included with the client device110 (though not shown in the schematic architecture diagram 300 of FIG.3 ) include one or more storage components, such as a hard disk drive, asolid-state storage device (SSD), a flash memory device, and/or amagnetic and/or optical disk reader; and/or a flash memory device thatmay store a basic input/output system (BIOS) routine that facilitatesbooting the client device 110 to a state of readiness; and a climatecontrol unit that regulates climate properties, such as temperature,humidity, and airflow.

The client device 110 may comprise a mainboard featuring one or morecommunication buses 312 that interconnect the processor 310, the memory301, and various peripherals, using a variety of bus technologies, suchas a variant of a serial or parallel AT Attachment (ATA) bus protocol;the Uniform Serial Bus (USB) protocol; and/or the Small Computer SystemInterface (SCI) bus protocol. The client device 110 may comprise adedicated and/or shared power supply 318 that supplies and/or regulatespower for other components, and/or a battery 304 that stores power foruse while the client device 110 is not connected to a power source viathe power supply 318. The client device 110 may provide power to and/orreceive power from other client devices.

In some scenarios, as a user 112 interacts with a software applicationon a client device 110 (e.g., an instant messenger and/or electronicmail application), descriptive content in the form of signals or storedphysical states within memory (e.g., an email address, instant messengeridentifier, phone number, postal address, message content, date, and/ortime) may be identified. Descriptive content may be stored, typicallyalong with contextual content. For example, the source of a phone number(e.g., a communication received from another user via an instantmessenger application) may be stored as contextual content associatedwith the phone number. Contextual content, therefore, may identifycircumstances surrounding receipt of a phone number (e.g., the date ortime that the phone number was received), and may be associated withdescriptive content. Contextual content, may, for example, be used tosubsequently search for associated descriptive content. For example, asearch for phone numbers received from specific individuals, receivedvia an instant messenger application or at a given date or time, may beinitiated. The client device 110 may include one or more servers thatmay locally serve the client device 110 and/or other client devices ofthe user 112 and/or other individuals. For example, a locally installedwebserver may provide web content in response to locally submitted webrequests. Many such client devices 110 may be configured and/or adaptedto utilize at least a portion of the techniques presented herein.

2. Presented Techniques

One or more computing devices and/or techniques for determining userintention-based representations associated with internet resourceidentification items and/or selecting content for transmission todevices are provided. For example, a user (and/or a device associatedwith the user) may access and/or interact with a service, such as abrowser, software, a website, an application, an operating system, etc.that provides a platform for viewing and/or downloading content from aserver associated with a content system. In some examples, the contentsystem may use user activity information associated with the user toselect content for presentation to the user. For example, the useractivity information may be indicative of web addresses of internetresources (e.g., web pages) accessed by the user. Accordingly,information indicative of characteristics of internet resources accessedby the user may be used to more accurately select content that the useris interested in.

Thus, in accordance with one or more of the techniques presented herein,a first internet resource identification item associated with one ormore first internet resources may be identified. In an example, thefirst internet resource identification item may comprise at least aportion of a domain name (e.g., a domain name of a website) associatedwith the one or more first internet resources and/or at least a portionof a web address (e.g., a uniform resource locator (URL)) associatedwith the one or more first internet resources. User activity informationassociated with a plurality of events may be analyzed to determine aplurality of sets of text associated with the first internet resourceidentification item, wherein each set of text of the plurality of setsof text is associated with an event, of the plurality of events,associated with an internet resource of the one or more first internetresources. In an example, the plurality of sets of text may comprise atleast one of search queries, product names, page titles, mail subjects,etc. A plurality of term representations may be determined based uponthe plurality of sets of text. A first user intention-basedrepresentation associated with the first internet resourceidentification item may be generated based upon the plurality of termrepresentations.

In some examples, content may be selected for transmission to one ormore client devices based upon the first user intention-basedrepresentation. For example, a first profile associated with the firstinternet resource identification item may be generated based upon thefirst user intention-based representation. The first profile may be usedfor selecting content for transmission to client devices that aredetermined to have accessed an internet resource of the one or morefirst internet resources (associated with the first internet resourceidentification item).

In some examples, the first profile may be generated based uponinformation associated with one or more other internet resourceidentification items, other than the first internet resourceidentification item. A plurality of user intention-based representationsassociated with a plurality of internet resource identification itemsmay be generated. The plurality of user intention-based representationsmay comprise the first user internet-based representation and/or theplurality of internet resource identification items may comprise thefirst internet resource identification item. A similarity profile may begenerated based upon the plurality of user intention-basedrepresentations. For example, the similarity profile may be indicativeof similarity scores corresponding to levels of similarity betweeninternet resource identification items of the plurality of internetresource identification items. A plurality of sets of informationassociated with a subset of internet resource identification items ofthe plurality of internet resource identification items may bedetermined (e.g., at least some information of one, some and/or all setsof information of the plurality of sets of information may be manuallycurated). Information of the plurality of sets of information may bepropagated to (e.g., included in) the first profile associated with thefirst internet resource identification item based upon the similarityprofile. For example, one or more sets of information, of the pluralityof sets of information, may be propagated to the first profile basedupon a determination that one or more similarity scores corresponding tolevels of similarity between the first internet resource identificationitem and one or more internet resource identification items meet (e.g.,are equal to or exceed) a threshold similarity score. In an example, theone or more sets of information included in the first profile may beindicative of characteristics of internet resources. The characteristicsmay be indicative of one or more intentions and/or one or more interestsof a user that accesses an internet resource associated with the firstinternet resource identification item. Due to propagation of the one ormore sets of information to the first profile, whether or not a userthat accessed an internet resource associated with the first internetresource identification item is part of a target audience of a contentitem may be more accurately determined. More accurately determiningwhether the user is part of the target audience of the content item mayresult in more accurately selection of a content item to the user.Alternatively and/or additionally, using the techniques provided hereinfor propagating information to profiles associated with internetresource identification items provides for determining profileinformation for internet resource identification items with at least oneof less manual effort, fewer computations, increased speed, etc., suchas due to not requiring that profile information (e.g., information tobe included in a profile associated with an internet resourceidentification item) be determined separately for each internet resourceidentification item of the plurality of internet resource identificationitems.

An embodiment of determining user intention-based representationsassociated with internet resource identification items and/or selectingcontent for transmission to devices is illustrated by an example method400 of FIG. 4 . At 402, a first internet resource identification itemassociated with one or more first internet resources may be identified.In an example, the first internet resource identification item maycomprise at least a portion of a domain name (e.g., a domain name of awebsite) associated with the one or more first internet resources and/orat least a portion of a web address (e.g., a uniform resource locator(URL)) associated with the one or more first internet resources. In anexample, an internet resource of the one or more first internetresources may be a web page that has a web address comprising and/ormatching the first internet resource identification item. In an example,the first internet resource identification item may be“floridastuff.com” (e.g., a domain name) and/or the one or more firstinternet resources may correspond to web pages that have web addressescomprising “floridastuff.com”, such as at least one of“www.floridastuff.com/index.html”,“www.floridastuff.com/fun-activities.html”, etc.

At 404, user activity information associated with a plurality of eventsmay be analyzed to determine a first plurality of search queriesassociated with the first internet resource identification item. In someexamples, the user activity information may be associated with a periodof time (e.g., the plurality of events may be events that are performedwithin the period of time), such as a period of 6 months, a period of 12months, a period of 13 months, or other period of time. In someexamples, the user activity information may be determined viaaggregating user activity of a plurality of users and/or a plurality ofclient devices (e.g., the plurality of events may comprise eventsassociated with different users and/or different client devices). Eachsearch query of the first plurality of search queries is associated withan event, of the plurality of events, in which an internet resource ofthe one or more first internet resources (associated with the firstinternet resource identification item) is accessed via a selection of asearch result from among search results generated based upon the searchquery.

FIGS. 5A-5I illustrate examples of an example system 501 for determininguser intention-based representations associated with internet resourceidentification items and/or selecting content for transmission todevices, described with respect to the method 400 of FIG. 4 . FIGS.5A-5C illustrate an example of a first event, of the plurality ofevents, in which an internet resource of the one or more first internetresources is accessed via a selection of a search result from amongsearch results generated based upon a search query.

FIG. 5A illustrates a first client device 500 presenting and/oraccessing a first web page 508 using a browser of the first clientdevice 500. The browser may comprise an address bar 502 comprising a webaddress (e.g., a uniform resource locator (URL)) of the first web page508. The first web page 508 may comprise a search interface. Forexample, the search interface may comprise a web search engine designedto search for information throughout the internet. In some examples, thefirst web page 508 may comprise a search field 506. For example, a firstsearch query “Theme Park” may be entered into the search field 506. Insome examples, the first web page 508 may comprise a search selectableinput 504 corresponding to performing a search based upon the firstsearch query. For example, the search selectable input 504 may beselected.

FIG. 5B illustrates the first client device 500 presenting a pluralityof search results associated with the first search query using thebrowser of the first client device 500. For example, the plurality ofsearch results may be presented within a second web page 518. Forexample, the plurality of search results may comprise a first searchresult 510 corresponding to a third web page, a second search result 512corresponding to a fourth web page 520 (illustrated in FIG. 5C), a thirdsearch result 514 corresponding to a fifth web page and/or a fourthsearch result 516 corresponding to a sixth web page. In some examples,each search result of the plurality of search results may comprise aselectable input (e.g., a link) corresponding to accessing a web pageassociated with the search result. In some examples, the second searchresult 512 corresponding to the fourth web page 520 may be selected(e.g., the second search result 512 may be selected via a secondselectable input corresponding to the second search result 512).

FIG. 5C illustrates the first client device 500 presenting and/oraccessing the fourth web page 520 in response to the selection of thesecond search result 512. In some examples, the user activityinformation may comprise a set of event information associated with thefirst event. For example, the set of event information may comprise anindication of the first search query (e.g., “Theme park”) entered intothe search interface and/or used to generate the plurality of searchresults. Alternatively and/or additionally, the set of event informationmay comprise an indication of a web address (e.g.,“www.searchinginterface.com/search?q=Theme+park”) of the second web page518 comprising the plurality of search results. Alternatively and/oradditionally, the set of event information may comprise an indication ofa web address (e.g., “floridastuff.com/Florida_Theme_Parks”) of thefourth web page 520 accessed via the selection of the second searchresult 512 from among the plurality of search results. It may bedetermined that the second web page 518 is associated with the firstinternet resource identification item based upon the web address of thefourth web page 520 (e.g., based upon a determination that the webaddress of the fourth web page 520 comprises the first internet resourceidentification item). Alternatively and/or additionally, the firstsearch query (e.g., “Theme park”) that led to the first client device500 accessing the second web page 518 may be determined based upon theset of event information. In an example, the first search query may bedetermined based upon, such as extracted from, the web address (e.g.,“www.searchinginterface.com/search?q=Theme+park”) of the second web page518 comprising the plurality of search results.

In an example, each event of the plurality of events may comprise aninternet resource (e.g., a web page) of the one or more first internetresources being accessed via a selection of a search result from amongsearch results generated based upon a search query. Other events (otherthan the first event) of the plurality of events may be identified usingone or more of the techniques provided herein with respect toidentifying the first event. Alternatively and/or additionally, othersearch queries (other than the first search query) of the firstplurality of search queries may be determined using one or more of thetechniques provided herein with respect to determining the first searchquery.

Search queries of the first plurality of search queries are related to(e.g., are reflective and/or indicative of) intentions, of users, inaccessing internet resources (e.g., web pages) associated with the firstinternet resource identification item. Using one or more of thetechniques provided herein, at least some of the first plurality ofsearch queries may be used to generate a first user intention-basedrepresentation associated with the first internet resourceidentification item.

In some examples, the first plurality of search queries is a subset ofsearch queries of a second plurality of search queries associated withthe first internet resource identification item. For example, eachsearch query of the second plurality of search queries is associatedwith an event, of the plurality of events, in which an internet resourceof the one or more first internet resources (associated with the firstinternet resource identification item) is accessed via a selection of asearch result from among search results generated based upon the searchquery. The subset of search queries may be selected from the secondplurality of search queries if a quantity of search queries, of thesecond plurality of search queries, exceeds a threshold quantity ofsearch queries k. Alternatively and/or additionally, if the quantity ofsearch queries of the second plurality of search queries does not exceedthe threshold quantity of search queries k, the first plurality ofsearch queries may comprise all of the second plurality of searchqueries. In some examples, a plurality of search query scores associatedwith the second plurality of search queries may be determined (e.g.,each search query score of the plurality of search query scores may beassociated with a search query of the second plurality of searchqueries). In an example, a first search query score (of the plurality ofsearch query scores) associated with the first search query may bedetermined based upon a measure of events, of the plurality of events,associated with the first search query. For example, the measure ofevents may correspond to a quantity and/or frequency of events, of theplurality of events, in which an internet resource of the one or morefirst internet resources (associated with the first internet resourceidentification item) is accessed via search results generated based uponthe first search query. In some examples, the first search query scoremay be based upon (e.g., may be equal to) the measure of eventsassociated with the first search query (e.g., the first search queryscore may be a function of the measure of events, wherein an increase ofthe measure of events results in an increase of the first search queryscore). Other search query scores of the plurality of search queryscores (other than the first search query score) may be determined usingone or more of the techniques provided herein with respect todetermining the first search query score.

The first plurality of search queries (used to generate the first userintention-based representation) may be selected from the secondplurality of search queries based upon the plurality of search queryscores. In some examples, the first plurality of search queries may beselected from the second plurality of search queries based upon adetermination that the first plurality of search queries are associatedwith highest search query scores of the plurality of search queryscores. Alternatively and/or additionally, the first plurality of searchqueries may be selected from the second plurality of search queriesbased upon a determination that the first plurality of search queriesare associated with k highest search query scores of the plurality ofsearch query scores (e.g., search queries associated with the k highestsearch query scores of the plurality of search query scores may beincluded in the first plurality of search queries). In an example wherek (e.g., the threshold quantity of search queries) is 1,000, 1,000search queries associated with 1,000 highest search query scores of theplurality of search query scores may be selected and/or included in thefirst plurality of search queries. Alternatively and/or additionally,the second plurality of search queries may be ranked based upon theplurality of search query scores (e.g., a search query having a highersearch query score of the plurality of search query scores is rankedhigher than a search query having a lower search query score of theplurality of search query scores), and/or the top k ranked searchqueries may be selected from among the second plurality of searchqueries (e.g., the top k ranked search queries may be included in thefirst plurality of search queries). Alternatively and/or additionally,the first plurality of search queries may be selected from the secondplurality of search queries based upon a determination that the firstplurality of search queries are associated with search query scores (ofthe plurality of search query scores) that meet (e.g., are equal to orexceed) a first threshold search query score (e.g., search queries thatare associated with search query scores, of the plurality of searchquery scores, that do not meet the first threshold search query score,may not be included in first plurality of search queries).

In some examples, a first search-to-click profile associated with thefirst internet resource identification item may be generated. The firstsearch-to-click profile may be generated based upon the user activityinformation associated with the plurality of events. In an example, thefirst search-to-click profile may be indicative of the second pluralityof search queries and/or the plurality of search query scores associatedwith the second plurality of search queries. FIG. 5D illustrates arepresentation 528 of the first search-to-click profile. In someexamples, the representation 528 may correspond to a graph, such as abipartite graph. The representation 528 may comprise relationship lines522 (e.g., edges). A relationship line of the relationship lines 522 maybe between a search query 526 of the second plurality of search queries(e.g., “theme park” 526A, “Florida entertainment” 526B, etc.) and thefirst internet resource identification item (shown with reference number524). A relationship line of the relationship lines 522 between a searchquery 526 and the first internet resource identification item 524 may beindicative of at least one event, of the plurality of events, havingoccurred in association with the search query 526 and the first internetresource identification item 524 (e.g., at least one event havingoccurred in which an internet resource of the one or more first internetresources associated with the first internet resource identificationitem 524 is accessed via search results generated based upon the searchquery 526).

In some examples, a relationship line of the relationship lines 522between a search query 526 and the first internet resourceidentification item 524 may have a weight (represented by thickness inFIG. 5D, for example) corresponding to a search query score associatedwith the search query 526. In an example, a first relationship line 522Aof the relationship lines 522 may be between a search query “theme park”526A and the first internet resource identification item 524. A secondrelationship line 522B of the relationship lines 522 may be between asearch query “Florida entertainment” 526B and the first internetresource identification item 524. A weight of the first relationshipline 522A (e.g., a search query score, of the plurality of search queryscores, associated with the search query “theme park” 526A) may begreater than a weight of the second relationship line 522B (e.g., asearch query score, of the plurality of search query scores, associatedwith the search query “Florida entertainment” 526B). Accordingly, ameasure (e.g., quantity and/or frequency) of events, of the plurality ofevents, associated with the search query “theme park” 526A may begreater than a measure (e.g., quantity and/or frequency) of events, ofthe plurality of events, associated with the search query “Floridaentertainment” 526B.

In an example in which the first plurality of search queries is a subsetof the second plurality of search queries, the first plurality of searchqueries may be selected from the second plurality of search queriesbased upon the first search-to-click profile.

At 406, a plurality of term representations may be determined based uponthe first plurality of search queries. In an example, the plurality ofterm representations may comprise at least one of one or more first termrepresentations of one or more first terms of the first search query ofthe first plurality of search queries, one or more second termrepresentations of one or more second terms of a second search query ofthe first plurality of search queries, etc.

In an example, a term of a search query may correspond to at least oneof a token, a word, a phrase, a portion, etc. of the search query. In anexample, a tokenization module may be used to split a search query ofthe first plurality of search queries into terms (e.g., words), whereinthe plurality of term representations may comprise term representationsof the terms. In an example in which the first search query is “themepark”, the one or more first terms of the first search query maycomprise a term “theme” and a term “park”. In some examples, one, someand/or all term representations of the plurality of term representationsare vector representations (e.g., embeddings and/or embedding-basedrepresentations) of terms of the first plurality of search queries. Inan example, one, some and/or all term representations of the pluralityof term representations are word vector representations (e.g., wordembeddings and/or word embedding-based representations) of words of thefirst plurality of search queries.

In some examples, the plurality of term representations may be generatedusing a term representation determination module. In an example, a termof a search query may be input to the term representation determinationmodule and the term representation determination module may output aterm representation, of the plurality of term representations, basedupon the term. In an example, the term representation determinationmodule may comprise a list of term representations associated with aplurality of terms, wherein a term representation of a term may be basedupon the list of term representations. In an example, the list of termrepresentations may comprise pre-trained term representations (e.g.,pre-trained word embeddings) associated with the plurality of terms. Inan example, the term representation determination module may useFasttext pre-trained word embeddings and/or other suitable pre-trainedword embeddings. The list of term representations may comprise termrepresentations for terms of multiple languages. For example, themultiple languages may comprise a first language and a second language.The list of term representations may comprise a first set of termrepresentations for terms of the first language and a second set of termrepresentations for terms of the second language. In some examples, thefirst set of term representations may be generated by a first modelassociated with the first language and/or the second set of termrepresentations may be generated by a second model associated with thesecond language. In an example, one or more first search queries of thefirst plurality of search queries may be in the first language and/orone or more second search queries of the first plurality of searchqueries may be in the second language. Term representations of the oneor more first search queries may be determined based upon the first setof term representations. Term representations of the one or more secondsearch queries may be determined based upon the second set of termrepresentations.

For example, the plurality of term representations may comprise aplurality of sets of term representations, wherein for each search queryof the first plurality of search queries, the plurality of sets of termrepresentations comprises a set of term representations comprising oneor more term representations of one or more terms of the search query.In an example, a first set of term representations of the plurality ofsets of term representations may comprise the one or more first termrepresentations of the one or more first terms of the first searchquery, a second set of term representations of the plurality of sets ofterm representations may comprise the one or more second termrepresentations of the one or more second terms of the second searchquery, etc.

In some examples, term representations of the plurality of termrepresentations are combined to generate a term representation datastructure associated with the first internet resource identificationitem 524. For example, some and/or all sets of term representations ofthe plurality of sets of term representations may be concatenated togenerate the term representation data structure. An example of the termrepresentation data structure (shown with reference number 532) is shownin FIG. 5E. The term representation data structure 532 may comprise theplurality of sets of term representations (shown with reference number530). In the example shown in FIG. 5E, the term representation datastructure 532 may comprise a set of term representations 530 aassociated with search query “query 1” of the first plurality of searchqueries, followed by a set of term representations 530 b associated withsearch query “query 2” of the first plurality of search queries,followed by a set of term representations 530 c associated with searchquery “query 3” of the first plurality of search queries, etc. In anexample, an order in which sets of term representations are arranged(e.g., concatenated) in the term representation data structure 532 isbased upon search query scores of the plurality of search query scores.For example, the sets of term representations may be arranged in theterm representation data structure 532 in decreasing order of searchquery scores, such as where the set of term representations 530 aassociated with search query “query 1” is arranged preceding (e.g.,ahead of, in front of, above, etc.) the set of term representations 530b associated with search query “query 2” due to a search query scoreassociated with search query “query 1” being higher than a search queryscore associated with search query “query 2”.

At 408, the first user intention-based representation associated withthe first internet resource identification item 524 may be generatedbased upon the plurality of term representations. For example, the firstuser intention-based representation may be generated based upon the termrepresentation data structure 532 (comprising concatenated sets of termrepresentations of the plurality of sets of term representations, forexample). In an example, the first user intention-based representationmay comprise a vector representation (e.g., an embedding and/or anembedding-based representation), such as a sentence embedding (e.g., anunordered sentence representation) generated based upon the termrepresentation data structure 532. FIG. 5E illustrates the first userintention-based representation (shown with reference number 536) beinggenerated. In an example, the term representation data structure 532 maybe input to a representation generation module 534. The representationgeneration module 534 may generate the first user intention-basedrepresentation 536 based upon the term representation data structure532.

In some examples, one or more operations (e.g., mathematical operations)are performed using term representations, of the term representationdata structure 532, to generate the first user intention-basedrepresentation 536. In an example, term representations of the termrepresentation data structure 532 may be averaged to generate the firstuser intention-based representation 536.

Alternatively and/or additionally, the first user intention-basedrepresentation 536 may be generated based upon a plurality of weightsassociated with the term representations of the term representation datastructure 532. For example, the term representations may be combined(e.g., averaged) based upon the plurality of weights to generate thefirst user intention-based representation 536. In an example, the firstuser intention-based representation 536 may be based upon a combination(e.g., a weighted average), of the term representations of the termrepresentation data structure 532, determined based upon the pluralityof weights (e.g., weighted averaging using the plurality of weights maybe performed based upon the term representations of the termrepresentation data structure 532 to generate the combination).

In some examples, the plurality of weights may be based upon a pluralityof metrics associated the term representations of the termrepresentation data structure 532. In an example, each metric of theplurality of metrics is associated with a term representation of theterm representation data structure 532 and corresponds to a measure(e.g., a quantity and/or frequency) of instances of a term, associatedwith the term representation, in a set of text. For example, theplurality of weights may comprise a first weight associated with a firstterm representation associated with the term “theme” (e.g., the firstterm representation is a representation, of the plurality of termrepresentations, of the term “theme”) and a second weight associatedwith a second term representation associated with the term “park” (e.g.,the second term representation is a representation, of the plurality ofterm representations, of the term “park”). The first weight may bedetermined based upon a first metric of the plurality of metrics. Thefirst metric may correspond to a measure of instances of the term“theme” in the set of text. For example, the first metric may correspondto a quantity of instances of the term “theme” in the set of text, suchas at least one of a quantity of times the term “theme” is referred toin the set of text, a quantity of sentences in the set of text thatcomprise the term “theme”, etc. Alternatively and/or additionally, thesecond weight may be determined based upon a second metric of theplurality of metrics. The second metric may correspond to a measure ofinstances of the term “park” in the set of text. In some examples, theset of text may comprise at least one of the second plurality of searchqueries, a text corpus, one or more articles, one or more encyclopedias,etc. In some examples, the first weight is determined based upon thefirst metric and/or the second weight is determined based upon thesecond metric. In an example, the first weight may be a function of thefirst metric. Alternatively and/or additionally, the second weight maybe a function of the second metric. In some examples, termrepresentations may be down-weighted proportional to term frequencies ofterms associated with the term representations. In an example, adecrease of the first metric results in an increase of the first weightand/or a decrease of the second metric may result in an increase of thesecond weight. Other weights of the plurality of weights (other than thefirst weight and the second weight) may be determined using one or moreof the techniques provided herein with respect to determining the firstweight and the second weight. In some examples, determining theplurality of weights using one or more of the techniques provided herein(such as where a decrease of a metric of the plurality of metricsresults in an increase of a weight determined based upon the metric) mayresult in more frequently used terms being de-emphasized and/or lessfrequently used terms being emphasized, wherein the less frequently usedterms may carry more semantic content than the more frequently usedterms, thereby increasing an isotropy of the combination and/or thefirst user intention-based representation 536 (such that the first userintention-based representation 536 is a contextualized representation,for example).

In some examples, one or more operations may be performed on thecombination (e.g., the weighted average) of the term representations ofthe term representation data structure 532 to generate the first userintention-based representation 536. For example, the one or moreoperations may be performed to remove noise of the combination (e.g.,smoothen the combination) to generate the first user intention-basedrepresentation 536. In some examples, one, some and/or all operations ofthe one or more operations may be performed using a smoothed inversefrequency (SIF) model and/or a different model. The noise of thecombination may be introduced to the combination by a set ofnoise-introducing terms in the first plurality of search queries. In anexample, the set of noise-introducing terms may comprise at least one ofone or more dataset-specific terms in the first plurality of searchqueries, one or more frequent terms in the first plurality of searchqueries (e.g., a quantity of instances of a frequent term of the one ormore frequent terms may exceed a threshold), one or more syntacticalfeatures in the first plurality of search queries, one or morestop-words (e.g., at least one of “a”, “the”, “is”, etc.) in the firstplurality of search queries, etc. The noise-introducing set of terms mayadd noise to the combination due to the additive property of termrepresentations of the plurality of term representations. In an example,the noise-introducing set of terms may amplify one or more signals ofthe combination in one or more dominant directions and/or may diminishone or more signals (e.g., useful signals) in one or more trailingdirections. In some examples, principal component analysis may beperformed on the combination to identify one or more principalcomponents of the combination, such as a top n principal components ofthe combination. In an example, n may be in the range of at least 1 toat most 10 (e.g., n may be equal to 5). In some examples, the one ormore operations may comprise removing the one or more principalcomponents from the combination. Alternatively and/or additionally, theone or more operations may comprise subtracting one or more weightedvector projections, associated with the one or more principalcomponents, from the combination. In some examples, a weight applied toa weighted vector projection of the one or more weighted vectorprojections may be a value (e.g., a singular value) that accounts for avariance of the one or more principal components. For example, the firstuser intention-based representation 536 may be generated by removing theone or more principal components from the combination and by subtractingthe one or more weighted vector projections from the combination. Insome examples, performing the one or more operations de-emphasizes morefrequently used terms and/or emphasizes less frequently used terms,wherein the less frequently used terms may carry more semantic contentthan the more frequently used terms, thereby increasing an isotropy ofthe first user intention-based representation 536.

In some examples, a plurality of user intention-based representationsassociated with a plurality of internet resource identification itemsmay be generated. For example, the plurality of user intention-basedrepresentations may comprise the first user intention-basedrepresentation 536 and/or the plurality of internet resourceidentification items may comprise the first internet resourceidentification item 524. In an example, each internet resourceidentification item of the plurality of internet resource identificationitems may be associated with one or more internet resources (such asdiscussed herein with respect to the first internet resourceidentification item 524 associated with the one or more first internetresources). In some examples, the plurality of user intention-basedrepresentations may comprise the first user intention-basedrepresentation 536 associated with the first internet resourceidentification item 524, a second user intention-based representationassociated with a second internet resource identification item (of theplurality of internet resource identification items), etc. Other userintention-based representations of the plurality of user intention-basedrepresentations (other than the first user intention-basedrepresentation 536) may be generated using one or more of the techniquesprovided herein with respect to generating the first userintention-based representation 536.

In some examples, the plurality of internet resource identificationitems may comprise multiple internet resource identification items thatare variants of a domain. For example, the multiple internet resourceidentification items may comprise at least one of differing domainsuffixes, differing domain prefixes, differing subdomains, differingpaths, etc. In an example, variants of the domain may be canonicalizedto determine the multiple internet resource identification items. In anexample, the domain may comprise “shoppingcenterforall”. The multipleinternet resource identification items may comprise differingsubdomains, such as a subdomain “careers” and/or a subdomain “shop”. Forexample, the multiple internet resource identification items maycomprise an internet resource identification item“careers.shoppingcenterforall.com” with the subdomain “careers”, and/oran internet resource identification item “shop.shoppingcenterforall.com”with the subdomain “shop”. The multiple internet resource identificationitems may comprise differing suffixes and/or prefixes associated with atleast one of different regions (e.g., “uk” for the United Kingdom, “ca”for Canada, etc.), different languages (e.g., “en” for English, “fr” forFrench, etc.), etc. For example, the multiple internet resourceidentification items may comprise at least one of an internet resourceidentification item “en.shoppingcenterforall.com” with the prefix “en”for English, an internet resource identification item“fr.shoppingcenterforall.com” with the prefix “fr” for French, etc. Themultiple internet resource identification items may comprise differingpaths associated with different parts of a website. For example, themultiple internet resource identification items may comprise at leastone of an internet resource identification item“www.shoppingcenterforall.com/electronics” associated with shopping forelectronics, an internet resource identification item“www.shoppingcenterforall.com/clothing” associated with shopping forclothing, etc.

In some examples, an instance of “www” in a web address (e.g., theinstance of “www” in “www.shoppingcenterforall.com”) may not beconsidered to be a subdomain. For example, the instance of “www” may beconsidered to be a part of a URL string. In an example, whether or not aweb address comprises “www” may not affect a determination of whichinternet resource identification item is associated with the webaddress. In an example, it may be determined that a web address“shoppingcenterforall.com” and a web address“www.shoppingcenterforall.com” are both associated with the sameinternet resource identification item “shoppingcenterforall.com”.Alternatively and/or additionally, a part of a web address that containsqualifying information about the web address (e.g., “careers” in“careers.shoppingcenterforall.com”, “shop” in“shop.shoppingcenterforall.com”, etc.) may be considered to be asubdomain.

In some examples, search queries associated with a third internetresource identification item of the multiple internet resourceidentification items may be supplemented with search queries associatedwith one or more other internet resource identification items of themultiple internet resource identifications. For example, a thirdplurality of search queries associated with the third internet resourceidentification item may be determined (using one or more of thetechniques provided herein with respect to determining the firstplurality of search queries and/or the second plurality of searchqueries, for example). A fourth plurality of search queries associatedwith a fourth internet resource identification item of the multipleinternet resource identification items may be determined (using one ormore of the techniques provided herein with respect to determining thefirst plurality of search queries and/or the second plurality of searchqueries, for example). In some examples, the third plurality of searchqueries may be supplemented with the fourth plurality of search queriessuch that a user intention-based representation associated with thethird internet resource identification item is determined based upon afifth plurality of search queries comprising the third plurality ofsearch queries and the fourth plurality of search queries. In someexamples, the third plurality of search queries may be supplemented withthe fourth plurality of search queries based upon a determination thatinternet resources associated with the third internet resourceidentification item and internet resources associated with the fourthinternet resource identification item fall under a same category.

In a first example, the third internet resource identification item is“shoppingcenterforall.com” and the fourth internet resourceidentification item is “shop.shoppingcenterforall.com”, wherein internetresources associated with the third internet resource identificationitem and internet resources associated with the fourth internet resourceidentification item are associated with an internet resource category“shopping” (e.g., both “shoppingcenterforall.com” and“shop.shoppingcenterforall.com” are used for shopping). In the firstexample, based upon the determination that internet resources associatedwith the third internet resource identification item and internetresources associated with the fourth internet resource identificationitem are associated with the internet resource category “shopping”, thethird plurality of search queries may be supplemented with the fourthplurality of search queries for determining the user intention-basedrepresentation associated with the third internet resourceidentification item.

In a second example, the third internet resource identification item is“shoppingcenterforall.com” and the fourth internet resourceidentification item is “careers.shoppingcenterforall.com”, whereininternet resources associated with the third internet resourceidentification item are associated with an internet resource category“shopping” and internet resources associated with the fourth internetresource identification item are associated with a different internetresource category “job search”. In the second example, based upon thedetermination that internet resources associated with the third internetresource identification item and internet resources associated with thefourth internet resource identification item are associated withdifferent internet resource categories, the third plurality of searchqueries may not be supplemented with the fourth plurality of searchqueries for determining the user intention-based representationassociated with the third internet resource identification item.

In a third example, the third internet resource identification item is“shoppingcenterforall.com/electronics” and the fourth internet resourceidentification item is “shoppingcenterforall.com/clothing”, whereininternet resources associated with the third internet resourceidentification item are associated with an internet resource category“electronics shopping” and internet resources associated with the fourthinternet resource identification item are associated with a differentinternet resource category “clothes shopping”. In the third example,based upon the determination that internet resources associated with thethird internet resource identification item and internet resourcesassociated with the fourth internet resource identification item areassociated with different internet resource categories, the thirdplurality of search queries may not be supplemented with the fourthplurality of search queries for determining the user intention-basedrepresentation associated with the third internet resourceidentification item.

In a fourth example, the third internet resource identification item is“shoppingcenterforall.com/electronics” and the fourth internet resourceidentification item is “electronicsstore.com”, wherein internetresources associated with the third internet resource identificationitem and internet resources associated with the fourth internet resourceidentification item are associated with an internet resource category“shopping” (e.g., both “shoppingcenterforall.com/electronics” and“electronicsstore.com” are used for shopping). In the fourth example,based upon the determination that internet resources associated with thethird internet resource identification item and internet resourcesassociated with the fourth internet resource identification item areassociated with the internet resource category “shopping”, the thirdplurality of search queries may be supplemented with the fourthplurality of search queries for determining the user intention-basedrepresentation associated with the third internet resourceidentification item (even though the third internet resourceidentification item and the fourth internet resource identification itemcomprise different domains, for example).

In some examples, a similarity profile may be generated based upon theplurality of user intention-based representations. For example, thesimilarity profile may be indicative of similarity scores correspondingto levels of similarity between internet resource identification itemsof the plurality of internet resource identification items. In anexample, a first similarity score of the similarity profile maycorrespond to a level of similarity between the first internet resourceidentification item 524 and the second internet resource identificationitem. The first similarity score may be based upon (e.g., may be equalto) a cosine similarity between the first user intention-basedrepresentation 536 associated with the first internet resourceidentification item 524 and the second user intention-basedrepresentation associated with the second internet resourceidentification item (e.g., the first user intention-based representation536 may be a first vector representation, the second userintention-based representation may be a second vector representation,and/or the first similarity score may correspond to a cosine similaritybetween the first vector representation and the second vectorrepresentation).

In some examples, using one or more of the techniques provided herein,the plurality of user intention-based representations (e.g., thesimilarity profile generated based upon the plurality of userintention-based representations) may be used for at least one ofcategorization of internet resource identification items, informationpropagation among profiles associated with internet resourceidentification items, grouping internet resource identification itemsinto groups, etc.

In an example, the plurality of internet resource identification itemsmay be grouped into a plurality of groups based upon the plurality ofuser intention-based representations. In an example, the plurality ofinternet resource identification items may be grouped into the pluralityof groups (based upon the plurality of user intention-basedrepresentations) using one or more clustering techniques, such as one ormore k-means clustering techniques and/or one or more other clusteringtechniques. Alternatively and/or additionally, the plurality of internetresource identification items may be grouped into the plurality ofgroups based upon the similarity scores of the similarity profile. Forexample, internet resource identification items may be grouped togetherin a first group of the plurality of groups based upon a determinationthat similarity scores corresponding to levels of similarity betweenuser intention-based representations associated with the internetresource identification items exceed a first threshold similarity score.Alternatively and/or additionally, the internet resource identificationitems may be grouped together in the first group based upon adetermination that the user intention-based representations associatedwith the internet resource identification items are top-m nearestneighbors, wherein m may be an integer (e.g., the determination that theuser intention-based representations are the top-m nearest neighbors maybe based upon the similarity scores corresponding to the levels ofsimilarity between the user intention-based representations).

In some examples, information propagation among profiles associated withinternet resource identification items of the plurality of internetresource identification items may be performed based upon the pluralityof groups. In an example, information (e.g., a category, a label,manually curated information, etc.) in a profile associated with aninternet resource identification item of a group of the plurality ofgroups may be propagated to one or more profiles of one or more otherinternet resource identification items in the group based upon theinternet resource identification item and the one or more other internetresource identification items belonging to the same group.

In an example, the first group may comprise the first internet resourceidentification item 524, the second internet resource identificationitem and/or one or more other internet resource identification items.First information (e.g., one or more characteristics, one or morelabels, manually curated information, etc.) associated with the secondinternet resource identification item may be determined. In an example,the first information may comprise one or more first characteristicsassociated with the second internet resource identification item, suchas one or more characteristics of internet resources associated with thesecond internet resource identification item. For example, the one ormore first characteristics may comprise one or more characteristics ofcontent of internet resources associated with the second internetresource identification item. In an example, the one or morecharacteristics may comprise one or more types of content provided byinternet resources associated with the second internet resourceidentification item (e.g., the one or more characteristics may compriseat least one of “educational content”, “news”, “videos”, “music”, etc.)and/or one or more topics of content provided by internet resourcesassociated with the second internet resource identification item (e.g.,the one or more characteristics may comprise at least one of “cars”,“accounting”, “real estate”, etc.). Alternatively and/or additionally,the one or more first characteristics may comprise one or morecharacteristics associated with one or more functionalities of internetresources associated with the second internet resource identificationitem (e.g., the one or more characteristics may comprise at least one of“shopping”, “searching”, etc.). In some examples, the one or more firstcharacteristics may correspond to labels from one or more firsttaxonomies, such as Interactive Advertising Bureau (IAB) taxonomy and/orone or more other taxonomies. In an example, the second internetresource identification item may correspond to a domain name of a website comprising educational information for preparing for a real estatecertification exam. In the example, the one or more firstcharacteristics may comprise at least one of “educational content”,“real estate”, “exam preparation”, etc. In some examples, the one ormore first characteristics may correspond to one or more intentionlabels associated with the second internet resource identification item.For example, the one or more first characteristics may be indicative ofone or more intentions and/or one or more interests of a user thataccesses an internet resource associated with the second internetresource identification item. In the example, based upon the one or morefirst characteristics, it may be determined that an intention of a userfor accessing an internet resource associated with the second internetresource identification item is to access educational content associatedwith real estate and/or to prepare for a real estate exam (and/or it maybe determined that a user that accesses an internet resource associatedwith the second internet resource identification item is interested ineducational content associated with real estate and/or is interested inpreparing for a real estate exam).

In some examples, the first information may be propagated to (e.g.,included in) a first profile associated with the first internet resourceidentification item 524 based upon the first internet resourceidentification item 524 and the second internet resource identificationitem belonging to the first group of the plurality of groups. Forexample, the first information may be propagated from a second profileassociated with the second internet resource identification item to thefirst profile and/or one or more other profiles associated with one ormore other internet resource identification items that belong to thefirst group. For example, the first profile associated with the firstinternet resource identification item 524 may be generated based uponthe first information (e.g., the first information may be included inthe first profile). In some examples, at least some of the firstinformation (e.g., one, some and/or all of the one or more firstcharacteristics) may be determined using manual effort (e.g., at leastsome of the first information may be produced by a labeling agent)and/or using one or more other techniques. Alternatively and/oradditionally, one or more internet resources associated with the secondinternet resource identification item may be analyzed to automaticallydetermine at least some of the first information (e.g., one, some and/orall of the one or more first characteristics), such as based uponcontent in the one or more internet resources (e.g., the content may beanalyzed using at least one of one or more natural language processing(NLP) techniques, one or more image analysis techniques, etc. todetermine at least some of the first information). Propagating the firstinformation to other profiles associated with other internet resourceidentification items of the first group provides for determining profileinformation for internet resource identification items of the firstgroup with at least one of less manual effort, fewer computations,increased speed, etc., such as due to not requiring that profileinformation (e.g., information to be included in a profile associatedwith an internet resource identification item) be determined separatelyfor each internet resource identification item of the first group.

Alternatively and/or additionally, a plurality of sets of informationassociated with a subset of internet resource identification items ofthe plurality of internet resource identification items may bedetermined. For example, the subset of internet resource identificationitems may correspond to a seed set of internet resource identificationitems, of the plurality of internet resource identification items, forwhich information (e.g., one or more characteristics) is determined,wherein at least some of the information is propagated to profiles ofinternet resource identification items (other than the subset ofinternet resource identification items, for example) of the plurality ofinternet resource identification items. In an example, at least someinformation of one, some and/or all sets of information of the pluralityof sets of information may be manually curated. In some examples, foreach internet resource identification item of the subset of internetresource identification items, the plurality of sets of information maycomprise a set of information associated with the internet resourceidentification item, wherein the set of information may comprise one ormore characteristics associated with the internet resourceidentification item (e.g., one or more characteristics of internetresources associated with the internet resource identification item,such as comprising at least one of one or more characteristics ofcontent associated with the internet resource identification item, oneor more types of content associated with the internet resourceidentification item, one or more topics of content associated with theinternet resource identification item, one or more characteristicsassociated with one or more functionalities of internet resourcesassociated with the internet resource identification item, one or morelabels from the one or more first taxonomies, one or more intentionlabels, etc.). In an example, the subset of internet resourceidentification items may comprise the second internet resourceidentification item, a third internet resource identification item, etc.The plurality of sets of information may comprise a first set ofinformation (e.g., the first information discussed above) associatedwith the second internet resource identification item, a second set ofinformation associated with the third internet resource identificationitem, etc. The plurality of sets of information may be determined usingone or more of the techniques provided herein with respect todetermining the first information.

In some examples, sets of information of the plurality of sets ofinformation may be propagated to profiles associated with internetresource identification items of the plurality of internet resourceidentification items based upon the similarity profile, such as basedupon similarity scores of the similarity profile.

In an example, the first set of information associated with the secondinternet resource identification item is propagated to profilesassociated with a relevant set of internet resource identificationitems. The relevant set of internet resource identification itemscorrespond to internet resource identification items that are determinedto be relevant to the first set of information and/or the secondinternet resource identification item. In an example, an internetresource identification item may be selected for inclusion in therelevant set of internet resource identification items based upon adetermination that a similarity score (as indicated by the similarityprofile, for example), corresponding to a level of similarity betweenthe internet resource identification item and the second internetresource identification item, meets (e.g., is equal to or exceeds) asecond threshold similarity score. For example, the first internetresource identification item 524 may be included in the relevant set ofinternet resource identification items based upon a determination thatthe first similarity score (corresponding to the level of similaritybetween the first internet resource identification item 524 and thesecond internet resource identification item) meets (e.g., is equal toor exceeds) the second threshold similarity score.

In some examples, the first profile associated with the first internetresource identification item 524 may be generated based upon theplurality of sets of information and similarity scores, of thesimilarity profile, corresponding to levels of similarity between thefirst internet resource identification item 524 and internet resourceidentification items of the subset of internet resource identificationitems. For example, one or more sets of information, of the plurality ofsets of information, may be selected for inclusion in the first profileassociated with the first internet resource identification item 524.FIG. 5F illustrates the one or more sets of information (shown withreference number 558) being included in the first profile (shown withreference number 560) associated with the first internet resourceidentification item 524. In an example, the one or more sets ofinformation 558 may comprise the first set of information (shown withreference number 542) associated with the second internet resourceidentification item and/or the second set of information (shown withreference number 546) associated with the third internet resourceidentification item. For example, the first set of information 542 maybe selected for inclusion in the first profile 560 associated with thefirst internet resource identification item 524 based upon adetermination that the first similarity score (corresponding to thelevel of similarity between the first internet resource identificationitem 524 and the second internet resource identification item) meets(e.g., is equal to or exceeds) the second threshold similarity score.Alternatively and/or additionally, the second set of information 546associated with the third internet resource identification item may beselected for inclusion in the first profile 560 based upon adetermination that a similarity score (corresponding to a level ofsimilarity between the first internet resource identification item 524and the third internet resource identification item) meets (e.g., isequal to or exceeds) the second threshold similarity score.

In some examples, a plurality of profiles associated with the pluralityof internet resource identification items may be generated. For example,the plurality of profiles may comprise the first profile 560, the secondprofile associated with the second internet resource identificationitem, etc. Other profiles of the plurality of profiles (other than thefirst profile 560) may be generated using one or more of the techniquesprovided herein with respect to generating the first profile 560. In anexample, information of the plurality of sets of information associatedwith the subset of internet resource identification items may bepropagated to profiles of the plurality of profiles (such as using oneor more of the techniques provided herein with respect to the firstprofile 560). In some examples, profiles of the plurality of profilesmay be used for content item selection (such as discussed herein withrespect to using the first profile 560 to select a first content itemfor presentation via the first client device 500).

In some examples, at least some of the plurality of profiles may be usedas training data for labeling internet resource identification items ofthe plurality of internet resource identification items with a set oflabels. For example, labels of the set of labels may be added toprofiles of the plurality of profile. In an example, the set of labelsmay correspond to labels from one or more second taxonomies differentthan the one or more first taxonomies. For example, labels of theplurality of profiles (e.g., labels from the one or more firsttaxonomies) may be mapped to the set of labels from the one or moresecond taxonomies. In some examples, a subset of profiles, of theplurality of profiles, may be used to label the internet resourceidentification items with the set of labels. The subset of profiles maycomprise profiles that are determined to meet a threshold quality, suchas profiles comprising one or more labels (indicative ofcharacteristics, such as the one or more first characteristics) thathave label confidence scores that meet (e.g., are equal to or exceed) athreshold label confidence score. Alternatively and/or additionally, thesubset of profiles may comprise profiles associated with internetresource identification items, of the plurality of internet resourceidentification items, that are associated with at least a thresholdamount of user activity (e.g., an internet resource identification itemmay be determined to be associated with at least the threshold amount ofuser activity if a measure of events in which internet resourcesassociated with the internet resource identification item are accessedexceeds a threshold measure of events).

At 410, a first content item may be selected for presentation via thefirst client device 500 based upon the first user intention-basedrepresentation 536. In some examples, the first content item may beselected and/or presented by a content system. The content system may bean advertisement system (e.g., an online advertising system).Alternatively and/or additionally, the content system may not be anadvertisement system. In some examples, the content system may providecontent items (e.g., advertisements, images, links, videos, etc.) to bepresented via pages associated with the content system. For example, thepages may be associated with websites (e.g., websites providing searchengines, email services, news content, communication services, etc.)associated with the content system. The content system may providecontent items to be presented in (dedicated) locations throughout thepages (e.g., one or more areas of the pages configured for presentationof content items). For example, a content item may be presented at thetop of a web page associated with the content system (e.g., within abanner area), at the side of the web page (e.g., within a column), in apop-up window, overlaying content of the web page, etc. Alternativelyand/or additionally, a content item may be presented within anapplication associated with the content system and/or within a gameassociated with the content system. Alternatively and/or additionally, auser may be required to consume and/or interact with the content itembefore the user can access content of a web page, utilize resources ofan application and/or play a game.

For example, the first content item may be selected for presentation viathe first client device 500 based upon the first profile 560 (that isdetermined based upon the first user intention-based representation536). For example, the first profile 560 may be used to select the firstcontent item for presentation via the first client device 500 based upona determination that the first client device 500 is associated with anevent (e.g., the first event shown in and/or described with respect toFIGS. 5A-5C) in which an internet resource (e.g., the fourth web page520) of the one or more first internet resources associated with thefirst internet resource identification item 524 is accessed. In anexample, the first event in which the fourth web page 520 is accessedmay be identified using a user profile, associated with the first clientdevice 500, indicative of internet resources accessed by the firstclient device 500 (e.g., the user profile may comprise an indication ofthe fourth web page 520 having been accessed by the first client device500). In an example, the user profile associated with the first clientdevice 500 may be used by the content system to select content items(e.g., advertisements and/or other type of content) for presentation viathe first client device 500.

In some examples, the first content item may be selected based uponfirst targeting information associated with the first content item andthe first profile 560 associated with the first internet resourceidentification item 524. In an example, the first targeting informationmay be indicative of information associated with a target audience ofthe first content item. In some examples, the first targetinginformation may be received from a second client device associated witha first entity associated with the first content item. In an example,the first entity may be an advertiser, a company, a brand, anorganization, etc. and/or the first content item may be an advertisementthat promotes the first entity and/or promotes one or more productsand/or services provided by the first entity. The first targetinginformation may be received via a targeting interface displayed via thesecond client device. For example, the targeting interface may compriseselectable inputs and/or text fields, wherein the first targetinginformation may be received via selections of the selectable inputsand/or text input via the text fields. In some examples, the firsttargeting information may be used to determine whether or not a user iswithin the target audience of the first content item.

In some examples, the first targeting information may comprise one ormore second characteristics associated with the target audience of thefirst content item. The one or more second characteristics may compriseone or more user activity characteristics of associated with the targetaudience (e.g., one or more characteristics of user activity of usersthat belong to the target audience). For example, the one or more useractivity characteristics may comprise at least one of one or more typesof content accessed by users of the target audience (e.g., the one ormore types of content may comprise at least one of “educationalcontent”, “news”, “videos”, “music”, etc.), one or more topics ofcontent accessed by users of the target audience (e.g., the one or moretopics of content may comprise at least one of “cars”, “accounting”,“real estate”, etc.), one or more internet resource functionalities ofinternet resources accessed by users of the target audience (e.g., theone or more internet resource functionalities may comprise at least oneof “shopping”, “searching”, etc.), one or more internet resourcesaccessed by users of the target audience, etc. In some examples, the oneor more second characteristics may correspond to labels from one or morethird taxonomies, such as IAB taxonomy and/or one or more othertaxonomies. In an example, the one or more third taxonomies may be thesame as the one or more first taxonomies. In some examples, the one ormore second characteristics may correspond to one or more intentionlabels associated with the target audience.

In some examples, whether or not the first client device 500 is part ofthe target audience of the first content item may be determined basedupon the user profile associated with the first client device 500 andthe first targeting information. For example, the user profile and/orthe first targeting information may be analyzed to identify one or morematching characteristics, such as one or more characteristics of useractivity of the first client device 500 that match one or morecharacteristics of user activity associated with the target audience. Insome examples, the one or more matching characteristics may bedetermined based upon one or more profiles associated with one or moreinternet resources accessed by the first client device 500 (as indicatedby the user profile associated with the first client device 500, forexample). For example, based upon the user profile being indicative ofthe first client device 500 having accessed the fourth web page 520associated with the first internet resource identification item 524, theone or more profiles may comprise the first profile 560 associated withthe first internet resource identification item 524.

In an example, the first profile 560 comprises the first set ofinformation 542 associated with the second internet resourceidentification item (such as shown in and/or described with respect toFIG. 5F). The first set of information 542 of the first profile 560 maybe compared with the first targeting information to determine the one ormore matching characteristics. In an example, the first set ofinformation 542 may comprise one or more characteristics of contentprovided by internet resources associated with the second internetresource identification item, wherein the one or more characteristicscomprise content topics comprising “theme park”, “tourism”, “traveling”and “entertainment”. The one or more second characteristics of the firsttargeting information may comprise content topics comprising “themepark”, “traveling”, “hotels” and “entertainment”. Accordingly, the oneor more matching characteristics may be determined to comprise contenttopics comprising “theme park”, “traveling” and “entertainment” (e.g.,the first content item may be an advertisement for a theme park). In anexample, it may be determined that the first client device 500 is partof the target audience of the first content item based upon the one ormore matching characteristics. In an example, based upon the profile 560and the first event in which the first client device 500 accesses thefourth web page associated with the first internet resourceidentification item 524, it may be determined that a user of the firstclient device 500 has an interest in content topics (e.g., “theme park”,“traveling” and “entertainment”) associated with the target audience ofthe first content item.

Alternatively and/or additionally, the first targeting information maybe indicative of one or more second internet resources associated withthe target audience (e.g., one or more second internet resourcesaccessed by users of the target audience). In an example, whether or notthe fourth web page 520 accessed by the first client device 500 (in thefirst event, for example) matches a second internet resource of the oneor more second internet resources may be determined based upon thesimilarity profile and/or the plurality of groups of internet resourceidentification items. For example, the fourth web page 520 may bedetermined to match the second internet resource based upon adetermination that the first internet resource identification item 524associated with the fourth web page 520 and an internet resourceidentification item associated with the second internet resource are inthe same group of the plurality of groups. For example, the plurality ofinternet resource identification items may comprise the internetresource identification item associated with the second internetresource (e.g., the internet resource identification item associatedwith the second internet resource may comprise a domain name of thesecond internet resource and/or at least a portion of a web address ofthe second internet resource). Alternatively and/or additionally, thefourth web page 520 may be determined to match the second internetresource based upon a determination that a similarity score (indicatedby the similarity profile) corresponding to a level of similaritybetween the first internet resource identification item 524 associatedwith the fourth web page 520 and the internet resource identificationitem associated with the second internet resource meets (e.g., is equalto or exceeds) a third threshold similarity score. In some examples, itmay be determined that the first client device 500 is part of the targetaudience of the first content item 500 based upon a determination thatthe fourth web page 520 accessed by the first client device 500 matchesthe second internet resource of the one or more second internetresources. In some examples, the one or more matching characteristicsmay comprise the fourth web page 520 and/or the second internet resourcebased upon a determination that the fourth web page 520 accessed by thefirst client device 500 matches the second internet resource of the oneor more second internet resources.

Whether or not the first client device 500 is part of the targetaudience of the first content item may be determined based upon the oneor more matching characteristics, such as based upon a quantity ofcharacteristics of the one or more matching characteristics. In anexample, the first client device 500 may be determined to be part of thetarget audience of the first content item based upon a determinationthat the quantity of characteristics of the one or more matchingcharacteristics meets (e.g., is equal to or exceeds) a thresholdquantity of characteristics. Alternatively and/or additionally, thefirst client device 500 may be determined to not be part of the targetaudience of the first content item based upon a determination that thequantity of characteristics of the one or more matching characteristicsdoes not meet (e.g., is less than) the threshold quantity ofcharacteristics. In an example, the threshold quantity ofcharacteristics may be one (e.g., the first client device 500 may bedetermined to be part of the target audience of the first content itembased upon identification of merely one matching characteristic betweenuser activity of the first client device 500 and user activity of thetarget audience as indicated by the first targeting information).Alternatively and/or additionally, the threshold quantity ofcharacteristics may be a value other than (e.g., greater than) one.

In some examples, the first content item may comprise at least one of anarticle, a video, an audio file, an image, a web page, an advertisement,an email, a message, a content suggestion, etc. In response to selectingthe first content item for presentation via the first client device 500,the first content item may be transmitted to the first client device500. The first content item may be displayed via the first client device500. Alternatively and/or additionally, in an example where the firstcontent item comprises audio, the audio may be played via the firstclient device 500 (e.g., the audio may be output via a speakerassociated with the first client device 500).

In some examples, the first content item may be selected forpresentation via the first client device 500 in response to receiving afirst request for content. The first request for content may be receivedin response to the first client device 500 accessing a second internetresource associated with the content system. For example, the firstclient device 500 may transmit a request to access the second internetresource to a server associated with the second internet resource. Inresponse to receiving the request to access the second internetresource, the server associated with the second internet resource maytransmit the first request for content to the content system (and/or toa server associated with the content system). Alternatively and/oradditionally, the first request for content may be received from thefirst client device 500. In some examples, the first request for contentmay correspond to a request to be provided with a content item (e.g., anadvertisement, an image, a link, a video, etc.) for presentation via thesecond internet resource.

FIGS. 5G-5I illustrate an exemplary scenario in which the first contentitem (shown with reference number 584 in FIG. 5I) is selected and/orpresented via the first client device 500. FIG. 5G illustrates the firstclient device 500 transmitting a request 566 to access a resource to afirst server 568. In some examples, the request 566 to access theresource may be transmitted in response to a selection of a selectableinput (such as a link) corresponding to a seventh web page 582 (shown inFIG. 5I). For example, the resource may correspond to the seventh webpage 582. The request 566 to access the resource may comprise anindication of the seventh web page 582 (e.g., a web address“https://stocks.exchange.com” of the seventh web page 582).Alternatively and/or additionally, the first server 568 may beassociated with the seventh web page 582.

FIG. 5H illustrates the first server 568 transmitting the first requestfor content (shown with reference number 574) to a second server 576associated with the content system. In some examples, the first requestfor content 574 may be transmitted (by the first server 568) in responseto receiving the request 566 to access the resource. Alternativelyand/or additionally, the first request for content 574 may betransmitted (to the second server 538) by the first client device 500.In some examples, the first request for content 574 may be a request tobe provided with a content item (e.g., an advertisement, an image, alink, a video, etc.) for presentation via the seventh web page 582.

In some examples, in response to receiving the first request for content574, the first content item 584 may be selected based upon adetermination that the first client device 500 is part of the targetaudience of the first content item 584, such as using one or more of thetechniques presented herein. In response to selecting the first contentitem 584 for presentation via the first client device 500, the firstcontent item 584 may be transmitted to the first client device 500 forpresentation via the seventh web page 582. FIG. 5I illustrates the firstclient device 500 presenting and/or accessing the seventh web page 582using the browser. For example, the content system may provide the firstcontent item 584 to be presented via the seventh web page 582 while theseventh web page 582 is accessed by the first client device 500.

An embodiment of determining user intention-based representationsassociated with internet resource identification items and/or selectingcontent for transmission to devices is illustrated by an example method600 of FIG. 6 . In some examples, the example method 600 may compriseimplementation of at least some of the techniques, features, etc.provided herein with respect to the example method 400 of FIG. 4 and/orthe example system 501 of FIGS. 5A-5I. For example, at least some of thetechniques, features, etc. provided herein with respect to searchqueries may be implemented with any type of set of text, such as atleast one of search queries, product names, page titles, mail subjects,etc.

At 602, a first internet resource identification item associated withone or more first internet resources may be identified. In an example,the first internet resource identification item may comprise at least aportion of a domain name (e.g., a domain name of a website, an emailaddress, etc.) associated with the one or more first internet resourcesand/or at least a portion of a web address (e.g., a uniform resourcelocator (URL)) associated with the one or more first internet resources.In an example, an internet resource of the one or more first internetresources may be a web page that has a web address comprising and/ormatching the first internet resource identification item. In an example,the first internet resource identification item may be“floridastuff.com” (e.g., a domain name) and/or the one or more firstinternet resources may correspond to web pages that have web addressescomprising “floridastuff.com”, such as at least one of“www.floridastuff.com/index.html”,“www.floridastuff.com/fun-activities.html”, etc. Alternatively and/oradditionally, an internet resource of the one or more first internetresources may be an email sent by an email account that has an emailaddress comprising and/or matching the first internet resourceidentification item. In an example, the first internet resourceidentification item may be “floridastuff.com” (e.g., a domain name)and/or the one or more first internet resources may correspond to emailsthat are sent by email accounts having email addresses comprising“floridastuff.com”, such as at least one of“marketing@floridastuff.com”, “customerservice@floridastuff.com”, etc.

In an example, the one or more first internet resources may comprise atleast one of one or more web pages, one or more websites, one or moreapplications, one or more articles, one or more videos, one or moreaudio files, one or more images, one or more web pages, one or moreadvertisements, one or more emails, one or more messages, etc.

At 604, user activity information associated with a plurality of eventsmay be analyzed to determine a first plurality of sets of textassociated with the first internet resource identification item. In someexamples, the user activity information may be associated with a periodof time (e.g., the plurality of events may be events that are performedwithin the period of time), such as a period of 6 months, a period of 12months, a period of 13 months, or other period of time. In someexamples, the user activity information may be determined viaaggregating user activity of a plurality of users and/or a plurality ofclient devices (e.g., the plurality of events may comprise eventsassociated with different users and/or different client devices). Eachset of text of the first plurality of sets of text is associated with anevent, of the plurality of events, associated with an internet resourceof the one or more first internet resources (associated with the firstinternet resource identification item).

In an example, sets of text of the first plurality of sets of textcomprise search queries (such as discussed herein with respect to theexample method 400 of FIG. 4 ). For example, a search query of the firstplurality of sets of text may be associated with an event, of theplurality of events, in which an internet resource of the one or morefirst internet resources is accessed via a selection of a search resultfrom among search results generated based upon the search query.

In an example, sets of text of the first plurality of sets of textcomprise product names. For example, a product name of the firstplurality of sets of text may be associated with an event, of theplurality of events, in which an internet resource (e.g., a web page) ofthe one or more first internet resources is accessed by a client device.The product name may be determined based upon a web address of theinternet resource (e.g., the web address may comprise an indication ofthe product name, wherein the product name may correspond to a name of aproduct that is sold on the internet resource). Alternatively and/oradditionally, the product name may be determined by analyzing content ofthe internet resource to identify the product name in the content. Insome examples, the event in which the internet resource is accessed(and/or the web address of the internet resource) may be determinedbased upon one or more received signals. The one or more receivedsignals may comprise a request, from the client device, to access theinternet resource. Alternatively and/or additionally, the one or morereceived signals may comprise a request for content. For example, therequest for content may correspond to a request to provide a contentitem (e.g., an advertisement) for presentation via the internet resourceon the client device. In an example, the request for content maycomprise an indication of the web address, wherein the event and/or theproduct name may be determined based upon the web address. In anexample, the request for content may be an advertisement requestreceived (by the content system, for example) from at least one of ademand-side platform (DSP), an ad exchange, a data exchange, etc.

In an example, sets of text of the first plurality of sets of textcomprise page titles. For example, a page title of the first pluralityof sets of text may be associated with an event, of the plurality ofevents, in which an internet resource (e.g., a web page) of the one ormore first internet resources is accessed by a client device. The pagetitle may be determined based upon a web address of the internetresource (e.g., the web address may comprise an indication of the pagetitle). Alternatively and/or additionally, the page title may bedetermined by analyzing content of the internet resource to identify thepage title in the content. The page title may correspond to a title ofcontent (e.g., a title of an article, a title of a video, etc.) that isprovided on the internet resource. In some examples, the event in whichthe internet resource is accessed (and/or the web address of theinternet resource) may be determined based upon one or more receivedsignals. The one or more received signals may comprise a request, fromthe client device, to access the internet resource. Alternatively and/oradditionally, the one or more received signals may comprise a requestfor content. For example, the request for content may correspond to arequest to provide a content item (e.g., an advertisement) forpresentation via the internet resource on the client device. In anexample, the request for content may comprise an indication of the webaddress, wherein the event and/or the page title may be determined basedupon the web address. In an example, the request for content may be anadvertisement request received (by the content system, for example) fromat least one of a DSP, an ad exchange, a data exchange, etc.

In an example, sets of text of the first plurality of sets of textcomprise mail subjects. For example, a mail subject of the firstplurality of sets of text may be associated with an event, of theplurality of events, in which an internet resource (e.g., an email) ofthe one or more first internet resources is transmitted by an emailaccount having an email address that comprises the first internetresource identification item. The mail subject may correspond to anemail subject of the internet resource (e.g., the email). The mailsubject may be determined based upon a subject field of the email.

In some examples, the first plurality of sets of text comprises multipletypes of sets of text, such as at least two of search queries, productnames, page titles, mail subjects, etc.

In some examples, the first plurality of sets of text comprises merelyone type of set of text, such as merely one of search queries, productnames, page titles, mail subjects, etc.

In some examples, the first plurality of sets of text is a subset ofsets of text of a second plurality of sets of text associated with thefirst internet resource identification item. For example, each set oftext of the second plurality of sets of text is associated with anevent, of the plurality of events, associated with an internet resourceof the one or more first internet resources. The subset of sets of textmay be selected from the second plurality of sets of text if a quantityof sets of text, of the second plurality of sets of text, exceeds athreshold quantity of sets of text k. Alternatively and/or additionally,if the quantity of sets of text of the second plurality of sets of textdoes not exceed the threshold quantity of sets of text k, the firstplurality of sets of text may comprise all of the second plurality ofsets of text. In some examples, a plurality of scores associated withthe second plurality of sets of text may be determined (e.g., each scoreof the plurality of scores may be associated with a set of text of thesecond plurality of sets of text). In an example, a first score (of theplurality of scores) associated with the first set of text may bedetermined based upon a measure of events, of the plurality of events,associated with the first set of text. For example, the measure ofevents may correspond to a quantity and/or frequency of events, of theplurality of events, associated with the first set of text. In anexample in which the first set of text is a product name, the measure ofevents may correspond to a quantity and/or frequency of events, of theplurality of events, in which an internet resource, of the one or morefirst internet resources, comprising an indication of the product nameis accessed. In some examples, the first score may be based upon (e.g.,may be equal to) the measure of events associated with the first set oftext (e.g., the first score may be a function of the measure of events,wherein an increase of the measure of events results in an increase ofthe first score). Other scores of the plurality of scores (other thanthe first score) may be determined using one or more of the techniquesprovided herein with respect to determining the first score.

The first plurality of sets of text (used to generate the first userintention-based representation) may be selected from the secondplurality of sets of text based upon the plurality of scores. In someexamples, the first plurality of sets of text may be selected from thesecond plurality of sets of text based upon a determination that thefirst plurality of sets of text are associated with highest scores ofthe plurality of scores. Alternatively and/or additionally, the firstplurality of sets of text may be selected from the second plurality ofsets of text based upon a determination that the first plurality of setsof text are associated with k highest scores of the plurality of scores(e.g., sets of text associated with the k highest scores of theplurality of scores may be included in the first plurality of sets oftext). In an example where k (e.g., the threshold quantity of sets oftext) is 1,000, 1,000 sets of text associated with 1,000 highest scoresof the plurality of scores may be selected and/or included in the firstplurality of sets of text. Alternatively and/or additionally, the secondplurality of sets of text may be ranked based upon the plurality ofscores (e.g., a set of text having a higher score of the plurality ofscores is ranked higher than a set of text having a lower score of theplurality of scores), and/or the top k ranked sets of text may beselected from among the second plurality of sets of text (e.g., the topk ranked sets of text may be included in the first plurality of sets oftext). Alternatively and/or additionally, the first plurality of sets oftext may be selected from the second plurality of sets of text basedupon a determination that the first plurality of sets of text areassociated with scores (of the plurality of scores) that meet (e.g., areequal to or exceed) a first threshold score (e.g., sets of text that areassociated with scores, of the plurality of scores, that do not meet thefirst threshold score, may not be included in first plurality of sets oftext).

At 606, a plurality of term representations may be determined based uponthe first plurality of sets of text. In an example, the plurality ofterm representations may comprise at least one of one or more first termrepresentations of one or more first terms of a first set of text of thefirst plurality of sets of text, one or more second term representationsof one or more second terms of a second set of text of the firstplurality of sets of text, etc.

In an example, a term of a set of text may correspond to at least one ofa token, a word, a phrase, a portion, etc. of the set of text. In anexample, a tokenization module may be used to split a set of text of thefirst plurality of sets of text into terms (e.g., words), wherein theplurality of term representations may comprise term representations ofthe terms. In some examples, one, some and/or all term representationsof the plurality of term representations are vector representations(e.g., embeddings and/or embedding-based representations) of terms ofthe first plurality of sets of text. In an example, one, some and/or allterm representations of the plurality of term representations are wordvector representations (e.g., word embeddings and/or wordembedding-based representations) of words of the first plurality of setsof text.

For example, the plurality of term representations may comprise aplurality of sets of term representations, wherein for each set of textof the first plurality of sets of text, the plurality of sets of termrepresentations comprises a set of term representations comprising oneor more term representations of one or more terms of the set of text. Inan example, a first set of term representations of the plurality of setsof term representations may comprise the one or more first termrepresentations of the one or more first terms of the first set of text,a second set of term representations of the plurality of sets of termrepresentations may comprise the one or more second term representationsof the one or more second terms of the second set of text, etc.

In some examples, term representations of the plurality of termrepresentations are combined to generate a term representation datastructure associated with the first internet resource identificationitem. In an example, some and/or all sets of term representations of theplurality of sets of term representations are concatenated to generatethe term representation data structure, such as using one or more of thetechniques provided herein with respect to the term representation datastructure 532.

At 608, a first user intention-based representation associated with thefirst internet resource identification item may be generated based uponthe plurality of term representations. For example, the first userintention-based representation may be generated based upon the termrepresentation data structure. The first user intention-basedrepresentation may be generated using one or more of the techniquesprovided with respect to act 408 of the example method 400.

In some examples, a plurality of user intention-based representationsassociated with a plurality of internet resource identification itemsmay be generated. For example, the plurality of user intention-basedrepresentations may comprise the first user intention-basedrepresentation and/or the plurality of internet resource identificationitems may comprise the first internet resource identification item. Inan example, each internet resource identification item of the pluralityof internet resource identification items may be associated with one ormore internet resources. In some examples, the plurality of userintention-based representations may comprise the first userintention-based representation associated with the first internetresource identification item, a second user intention-basedrepresentation associated with a second internet resource identificationitem (of the plurality of internet resource identification items), etc.

In some examples, using one or more of the techniques provided herein,user intention-based representations of the plurality of userintention-based representations are generated in an unsupervised manner,thereby providing for less (and/or zero) manual effort required togenerate the plurality of user intention-based representations.

In some examples, a similarity profile may be generated based upon theplurality of user intention-based representations. For example, thesimilarity profile may be indicative of similarity scores correspondingto levels of similarity between internet resource identification itemsof the plurality of internet resource identification items.

In some examples, using one or more of the techniques provided herein,the plurality of user intention-based representations (e.g., thesimilarity profile generated based upon the plurality of userintention-based representations) may be used for at least one ofcategorization of internet resource identification items, informationpropagation among profiles associated with internet resourceidentification items, grouping internet resource identification itemsinto groups, etc.

In an example, a first profile associated with the first internetresource identification item may be generated based upon informationdetermined for one or more other internet resource identification itemsof the plurality of internet resource identification items. For example,the information associated with the one or more other internet resourceidentification items may be propagated to the first profile associatedwith the first internet resource identification item (such as using oneor more of the techniques provided herein with respect to the examplemethod 400 of FIG. 4 , such as generating the first profile 560 and/orincluding the one or more sets of information 558 in the first profile560).

At 610, a first content item may be selected for presentation via afirst client device based upon the first user intention-basedrepresentation. For example, the first content item may be selected forpresentation via the first client device based upon the first profile(that is determined based upon the first user intention-basedrepresentation). For example, the first content item may be selected forpresentation via the first client device based upon the first profileand/or first targeting information associated with the first contentitem (such as using one or more of the techniques provided herein withrespect to act 410 of the example method 400). In some examples, thefirst content item may be selected and/or presented by a content system.

In some examples, the first content item may comprise at least one of anarticle, a video, an audio file, an image, a web page, an advertisement,an email, a message, a content suggestion, etc. In response to selectingthe first content item for presentation via the first client device, thefirst content item may be transmitted to the first client device. Thefirst content item may be displayed via the first client device.Alternatively and/or additionally, in an example where the first contentitem comprises audio, the audio may be played via the first clientdevice (e.g., the audio may be output via a speaker associated with thefirst client device).

In some examples, the first content item may be selected forpresentation via the first client device in response to receiving afirst request for content. The first request for content may be receivedin response to the first client device accessing a second internetresource associated with the content system. For example, the firstclient device may transmit a request to access the second internetresource to a server associated with the second internet resource. Inresponse to receiving the request to access the second internetresource, the server associated with the second internet resource maytransmit the first request for content to the content system (and/or toa server associated with the content system). Alternatively and/oradditionally, the first request for content may be received from thefirst client device. In some examples, the first request for content maycorrespond to a request to be provided with a content item (e.g., anadvertisement, an image, a link, a video, etc.) for presentation via thesecond internet resource.

In an example, the first internet resource identification item maycorrespond to a domain name of one or more email addresses. The firstprofile associated with the first internet resource identification itemmay be used for selecting the first content item (in response to thefirst request for content, for example) based upon a determination thatthe first client device is associated with an event associated with thefirst internet resource identification item. In an example, the eventmay comprise an email associated with the first internet resourceidentification item being sent to an email account associated with thefirst client device and/or the email being accessed via an emailinterface on the first client device. In an example, it may bedetermined that the email is associated with the first internet resourceidentification item based upon a determination that an email address ofan email sender of the email comprises and/or matches the first internetresource identification item (e.g., the first internet resourceidentification item may comprise “floridastuff.com” and/or the emailaddress of the email sender may be “marketing@floridastuff.com”). In anexample, the first profile is indicative of one or more characteristicsof content provided by emails associated with the first internetresource identification item (e.g., emails that are sent by emailaddresses that comprise and/or match the first internet resourceidentification item). The one or more characteristics indicated by thefirst profile may be compared with one or more characteristics of thefirst targeting information to determine one or more matchingcharacteristics, wherein whether or not the first client device is partof a target audience of the first content item is determined based uponthe one or more matching characteristics. The first content item may beselected for presentation via the first client device based upon adetermination that the first client device is part of the targetaudience of the first content item.

It may be appreciated that the disclosed subject matter may assist auser (and/or a client device associated with the user) in receivingand/or consuming content that the user may have an interest in. Forexample, the content selected for transmission to the client device maybe selected based upon a determination that the user is part of a targetaudience of the content. Accordingly, a probability that the user isinterested in the content may be increased.

Implementation of at least some of the disclosed subject matter may leadto benefits including, but not limited to, more accurate selection ofcontent items for presentation via client devices (e.g., as a result ofgenerating the plurality of user intention-based representationsassociated with the plurality of internet resource identification items,as a result of generating the similarity profile associated with theplurality of internet resource identification items based upon theplurality of user intention-based representations, as a result ofpropagating information associated with one or more internet resourceidentification items to a profile associated with an internet resourceidentification item based upon the similarity profile such that theprofile associated with the internet resource identification item has anincreased amount of information, as a result of selecting content forpresentation via a client device based upon the profile with theincreased amount of information, etc.).

Alternatively and/or additionally, implementation of the disclosedsubject matter may lead to benefits including determining profileinformation associated with internet resource identification items witha reduced amount of manual effort (e.g., as a result of using thesimilarity profile to propagate information associated with one or moreinternet resource identification items to profiles associated with otherinternet resource identification items such that information does notneed to be manually determined separately for each internet resourceidentification item of the plurality of internet resource identificationitems).

Alternatively and/or additionally, implementation of the disclosedsubject matter may lead to benefits including increased user privacy(e.g., as a result of generating the plurality of user intention-basedrepresentations using aggregated user data on an aggregate level suchthat the user-intention based representations may be user-agnostic).

Alternatively and/or additionally, implementation of the disclosedsubject matter may lead to benefits including an increase in generalizedrevenue for presenting content items via client devices (e.g., as aresult of more accurately selecting content items for presentation viaclient devices such that a probability of receiving a positive signalresponsive to presentation of a selected content item (e.g., anadvertisement click, a conversion event, etc.), and/or a probability ofreceiving revenue as a result of the positive signal, are increased dueto the more accurate selection of the content items).

Alternatively and/or additionally, implementation of at least some ofthe disclosed subject matter may lead to benefits including a reductionin screen space and/or an improved usability of a display (e.g., of aclient device) (e.g., as a result of enabling a user of the clientdevice to automatically consume content associated with subject matterthat the user has an interest in, wherein the user may not view contentthat the user does not have an interest in, wherein the user may notneed to open a separate application and/or a separate window in order tofind content having the subject matter that the user has an interest in,etc.).

Alternatively and/or additionally, implementation of at least some ofthe disclosed subject matter may lead to benefits including a reductionin bandwidth (e.g., as a result of reducing a need for the user to opena separate application and/or a separate window in order to searchthroughout the internet and/or navigate through internet content to findcontent that the user has an interest in).

Alternatively and/or additionally, implementation of at least some ofthe disclosed subject matter may lead to benefits including a moreaccurate and precise control of transmission of content items tointended users (e.g., as a result of more accurately determining that auser is part of a target audience of a content item and/or selecting thecontent item based upon the more accurate determination, etc.).

In some examples, at least some of the disclosed subject matter may beimplemented on a client device, and in some examples, at least some ofthe disclosed subject matter may be implemented on a server (e.g.,hosting a service accessible via a network, such as the Internet).

FIG. 7 is an illustration of a scenario 700 involving an examplenon-transitory machine readable medium 702. The non-transitory machinereadable medium 702 may comprise processor-executable instructions 712that when executed by a processor 716 cause performance (e.g., by theprocessor 716) of at least some of the provisions herein (e.g.,embodiment 714). The non-transitory machine readable medium 702 maycomprise a memory semiconductor (e.g., a semiconductor utilizing staticrandom access memory (SRAM), dynamic random access memory (DRAM), and/orsynchronous dynamic random access memory (SDRAM) technologies), aplatter of a hard disk drive, a flash memory device, or a magnetic oroptical disc (such as a compact disc (CD), digital versatile disc (DVD),or floppy disk). The example non-transitory machine readable medium 702stores computer-readable data 704 that, when subjected to reading 706 bya reader 710 of a device 708 (e.g., a read head of a hard disk drive, ora read operation invoked on a solid-state storage device), express theprocessor-executable instructions 712. In some embodiments, theprocessor-executable instructions 712, when executed, cause performanceof operations, such as at least some of the example method 400 of FIG. 4and/or at least some of the example method 600 of FIG. 6 , for example.In some embodiments, the processor-executable instructions 712 areconfigured to cause implementation of a system, such as at least some ofthe example system 501 of FIGS. 5A-5I, for example.

3. Usage of Terms

As used in this application, “component,” “module,” “system”,“interface”, and/or the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a controller and the controller can be a component. One or morecomponents may reside within a process and/or thread of execution and acomponent may be localized on one computer and/or distributed betweentwo or more computers.

Unless specified otherwise, “first,” “second,” and/or the like are notintended to imply a temporal aspect, a spatial aspect, an ordering, etc.Rather, such terms are merely used as identifiers, names, etc. forfeatures, elements, items, etc. For example, a first object and a secondobject generally correspond to object A and object B or two different ortwo identical objects or the same object.

Moreover, “example” is used herein to mean serving as an instance,illustration, etc., and not necessarily as advantageous. As used herein,“or” is intended to mean an inclusive “or” rather than an exclusive“or”. In addition, “a” and “an” as used in this application aregenerally be construed to mean “one or more” unless specified otherwiseor clear from context to be directed to a singular form. Also, at leastone of A and B and/or the like generally means A or B or both A and B.Furthermore, to the extent that “includes”, “having”, “has”, “with”,and/or variants thereof are used in either the detailed description orthe claims, such terms are intended to be inclusive in a manner similarto the term “comprising”.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing at least some of the claims.

Furthermore, the claimed subject matter may be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. Of course, manymodifications may be made to this configuration without departing fromthe scope or spirit of the claimed subject matter.

Various operations of embodiments are provided herein. In an embodiment,one or more of the operations described may constitute computer readableinstructions stored on one or more computer and/or machine readablemedia, which if executed will cause the operations to be performed. Theorder in which some or all of the operations are described should not beconstrued as to imply that these operations are necessarily orderdependent. Alternative ordering will be appreciated by one skilled inthe art having the benefit of this description. Further, it will beunderstood that not all operations are necessarily present in eachembodiment provided herein. Also, it will be understood that not alloperations are necessary in some embodiments.

Also, although the disclosure has been shown and described with respectto one or more implementations, equivalent alterations and modificationswill occur to others skilled in the art based upon a reading andunderstanding of this specification and the annexed drawings. Thedisclosure includes all such modifications and alterations and islimited only by the scope of the following claims. In particular regardto the various functions performed by the above described components(e.g., elements, resources, etc.), the terms used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., that is functionally equivalent), even though notstructurally equivalent to the disclosed structure. In addition, while aparticular feature of the disclosure may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.

What is claimed is:
 1. A method, comprising: identifying a firstinternet resource identification item associated with one or more firstinternet resources; analyzing user activity information associated witha plurality of events to determine a plurality of search queriesassociated with the first internet resource identification item, whereineach search query of the plurality of search queries is associated withan event, of the plurality of events, in which an internet resource ofthe one or more first internet resources is accessed via a selection ofa search result from among search results generated based upon thesearch query; determining a plurality of term representations based uponthe plurality of search queries, wherein the plurality of termrepresentations comprises: one or more first term representations of oneor more first terms of a first search query of the plurality of searchqueries; and one or more second term representations of one or moresecond terms of a second search query of the plurality of searchqueries; generating, based upon the plurality of term representations, afirst user intention-based representation associated with the firstinternet resource identification item; and selecting a first contentitem for presentation via a first client device based upon the firstuser intention-based representation.
 2. The method of claim 1, whereinthe determining the plurality of search queries comprises: determining asecond plurality of search queries, associated with the first internetresource identification item, based upon the user activity information,wherein the second plurality of search queries comprises the pluralityof search queries; and determining a plurality of search query scoresassociated with the second plurality of search queries, wherein thedetermining the plurality of search query scores comprises: determininga first search query score, of the plurality of search query scores,associated with the first search query based upon a measure of events,of the plurality of events, associated with the first search query; anddetermining a second search query score, of the plurality of searchquery scores, associated with the second search query based upon ameasure of events, of the plurality of events, associated with thesecond search query.
 3. The method of claim 2, comprising: selecting theplurality of search queries, from the second plurality of searchqueries, based upon the plurality of search query scores.
 4. The methodof claim 1, comprising: generating, based upon the first userintention-based representation and a plurality of user intention-basedrepresentations, a similarity profile indicative of similarity scorescorresponding to levels of similarity between internet resourceidentification items of a second plurality of internet resourceidentification items.
 5. The method of claim 1, wherein: the firstcontent item is selected based upon one or more first characteristicsassociated with a second internet resource identification item in a samegroup as the first internet resource identification item.
 6. The methodof claim 5, wherein: the first targeting information comprises one ormore second characteristics associated with a target audience of thefirst content item.
 7. The method of claim 1, comprising: generating,based upon the first user intention-based representation and a pluralityof user intention-based representations, a similarity profile indicativeof similarity scores corresponding to levels of similarity betweeninternet resource identification items of a second plurality of internetresource identification items comprising the first internet resourceidentification item and the plurality of internet resourceidentification items; and determining a plurality of sets of informationassociated with a subset of internet resource identification items ofthe second plurality of internet resource identification items.
 8. Themethod of claim 7, comprising: generating a profile associated with thefirst internet resource identification item based upon the plurality ofsets of information and similarity scores, of the similarity profile,corresponding to levels of similarity between the first internetresource identification item and internet resource identification itemsof the subset of internet resource identification items.
 9. The methodof claim 1, comprising: in response to the selecting the first contentitem for presentation via the first client device, transmitting thefirst content item to the first client device.
 10. The method of claim1, comprising: determining, based upon a plurality of metrics associatedwith term representations of the plurality of term representations,weights associated with the term representations, wherein: a metric ofthe plurality of metrics is associated with a term representation of theplurality of term representations and corresponds to a measure ofinstances of a term associated with the term representation in a set oftext; and the generating the first user intention-based representationis based upon the weights.
 11. The method of claim 10, wherein: thegenerating the first user intention-based representation comprisescombining the plurality of term representations based upon the weights.12. The method of claim 1, wherein: the selecting the first content itemfor presentation via the first client device is performed in response toreceiving a first request for content associated with the first clientdevice.
 13. A computing device comprising: a processor; and memorycomprising processor-executable instructions that when executed by theprocessor cause performance of operations, the operations comprising:identifying a first internet resource identification item associatedwith one or more first internet resources; analyzing user activityinformation associated with a plurality of events to determine aplurality of sets of text associated with the first internet resourceidentification item, wherein each set of text of the plurality of setsof text is associated with an event, of the plurality of events,associated with an internet resource of the one or more first internetresources; determining a plurality of term representations based uponthe plurality of sets of text, wherein the plurality of termrepresentations comprises: one or more first term representations of oneor more first terms of a first set of text of the plurality of sets oftext; and one or more second term representations of one or more secondterms of a second set of text of the plurality of sets of text;generating, based upon the plurality of term representations, a firstuser intention-based representation associated with the first internetresource identification item; and selecting a first content item forpresentation via a first client device based upon the first userintention-based representation.
 14. The computing device of claim 13,the determining the plurality of sets of text comprises: determining asecond plurality of sets of text, associated with the first internetresource identification item, based upon the user activity information,wherein the second plurality of sets of text comprises the plurality ofsets of text; determining a plurality of scores associated with thesecond plurality of sets of text, wherein the determining the pluralityof scores comprises: determining a first score, of the plurality ofscores, associated with the first set of text based upon a measure ofevents, of the plurality of events, associated with the first set oftext; and determining a second score, of the plurality of scores,associated with the second set of text based upon a measure of events,of the plurality of events, associated with the second set of text; andselecting the plurality of sets of text, from the second plurality ofsets of text, based upon the plurality of scores.
 15. The computingdevice of claim 13, the operations comprising: generating, based uponthe first user intention-based representation and a plurality of userintention-based representations, a similarity profile indicative ofsimilarity scores corresponding to levels of similarity between internetresource identification items of a second plurality of internet resourceidentification items.
 16. The computing device of claim 13, wherein: thefirst content item is selected based upon one or more firstcharacteristics associated with a second internet resourceidentification item in a same group as the first internet resourceidentification item.
 17. The computing device of claim 13, theoperations comprising: generating, based upon the first userintention-based representation and a plurality of user intention-basedrepresentations, a similarity profile indicative of similarity scorescorresponding to levels of similarity between internet resourceidentification items of a second plurality of internet resourceidentification items comprising the first internet resourceidentification item and the plurality of internet resourceidentification items; determining a plurality of sets of informationassociated with a subset of internet resource identification items ofthe second plurality of internet resource identification items; andgenerating a profile associated with the first internet resourceidentification item based upon the plurality of sets of information andsimilarity scores, of the similarity profile, corresponding to levels ofsimilarity between the first internet resource identification item andinternet resource identification items of the subset of internetresource identification items.
 18. A non-transitory machine readablemedium having stored thereon processor-executable instructions that whenexecuted cause performance of operations, the operations comprising:identifying a first internet resource identification item associatedwith one or more first internet resources; analyzing user activityinformation associated with a plurality of events to determine aplurality of sets of text associated with the first internet resourceidentification item, wherein each set of text of the plurality of setsof text is associated with an event, of the plurality of events,associated with an internet resource of the one or more first internetresources; determining a plurality of term representations based uponthe plurality of sets of text, wherein the plurality of termrepresentations comprises: one or more first term representations of oneor more first terms of a first set of text of the plurality of sets oftext; and one or more second term representations of one or more secondterms of a second set of text of the plurality of sets of text;generating, based upon the plurality of term representations, a firstuser intention-based representation associated with the first internetresource identification item; and selecting a first content item forpresentation via a first client device based upon the first userintention-based representation.
 19. The non-transitory machine readablemedium of claim 18, the operations comprising: identifying an event,associated with the first client device, in which an internet resourceof the one or more first internet resources associated with the firstinternet resource identification item is accessed, wherein the selectingthe first content item for presentation via the first client device isbased upon first targeting information associated with the first contentitem.
 20. The non-transitory machine readable medium of claim 19, theoperations comprising: in response to the selecting the first contentitem for presentation via the first client device, transmitting thefirst content item to the first client device.